Kate Culhane, Dept. of Ecology, Evolution, and Marine Biology, UC Santa Barbara
kathrynculhane@ucsb.edu
Summary
Exploring the data
DEPENDENCIES
##### PACKAGES #####
library(tidyverse) # data manipulation & visualization
library(vegan) # community analyses
library(goeveg) # scree plot for NMDS
##### DATA #####
# Invertebrate counts by order from sticky and pitfall trap samples
prey <- read_csv("output/02_prey.csv")
# Invertebrate counts by order from lizard stomach pumping samples
diet <- read_csv("output/02_diet_inverts.csv")
# Site by species matrix (invert prey data)
prey_matrix <- read_csv("output/02_prey_matrix.csv")
# Site by species matrix (diet data)
diet_matrix <- read_csv("output/02_diet_matrix.csv")# Summary table
prey %>%
group_by(order, trap_type) %>%
summarise(n = sum(count)) %>%
pivot_wider(names_from = trap_type, values_from = n) %>%
mutate(total = pitfall + sticky) %>%
arrange(-total)# Abundance by order
prey %>%
ggplot(aes(x = trap_type, y = count)) +
geom_jitter(aes(color = trap_type),
width = 0.1, size = 1.5) +
geom_boxplot(fill = NA, outlier.shape = NA) +
facet_wrap(~ fct_reorder(order, count, .fun = sum, .desc = TRUE),
scales = "free_y") +
theme_classic() +
theme(legend.position = "NA") +
labs(x = "Trap type", y = "Abundance (indv/trap)")# Summary table
diet %>%
group_by(order) %>%
summarise(n = sum(count)) %>%
arrange(-n)# Abundance by order
diet %>%
# Data wrangling
group_by(order) %>%
mutate(n = length(count)) %>%
# Plot
ggplot(aes(x = fct_reorder(order, count, .fun = sum, .desc = TRUE), y = count)) +
geom_jitter(width = 0.1, size = 1.5) +
geom_boxplot(fill = NA, outlier.shape = NA) +
geom_text(aes(y = 80, label = paste("n =", n)),
stat = "unique", angle = 90, size = 3) +
scale_y_log10() +
theme_classic() +
theme(legend.position = "NA",
axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)) +
labs(x = "Order", y = "Abundance (indv/lizard)")# Wrangle matrix
m_p <- as.matrix(prey_matrix[-c(1:4)])
rownames(m_p) <- prey_matrix$sample
m_p_hell <- decostand(m_p, 'hellinger') # Hellinger transformation
m_p_meta <- select(prey_matrix, sample, site, trap, trap_type) # metadata
# Scree plot to check stress per number of dimensions
dimcheckMDS(m_p_hell, distance = "bray", autotransform = FALSE, k = 10)# Create NMDS ordination
ord <- metaMDS(m_p_hell,
distance = 'bray', # use Bray-Curtis distances
autotransform = FALSE, # already manually transformed the matrix
k = 3, # number of dimensions
trymax = 1000)
# Stress plot
stressplot(ord)## Run 0 stress 0.2455473
## Run 1 stress 0.2232751
## ... New best solution
## ... Procrustes: rmse 0.01714159 max resid 0.1989876
## Run 2 stress 0.2299027
## Run 3 stress 0.4715637
## Run 4 stress 0.2402168
## Run 5 stress 0.2231786
## ... New best solution
## ... Procrustes: rmse 0.002964788 max resid 0.02966872
## Run 6 stress 0.2362589
## Run 7 stress 0.2232164
## ... Procrustes: rmse 0.00430651 max resid 0.04670683
## Run 8 stress 0.2227869
## ... New best solution
## ... Procrustes: rmse 0.005050154 max resid 0.06800828
## Run 9 stress 0.222782
## ... New best solution
## ... Procrustes: rmse 0.0003702364 max resid 0.002786871
## ... Similar to previous best
## Run 10 stress 0.2230862
## ... Procrustes: rmse 0.005521183 max resid 0.06134435
## Run 11 stress 0.2414472
## Run 12 stress 0.2295934
## Run 13 stress 0.2230211
## ... Procrustes: rmse 0.005498272 max resid 0.06124748
## Run 14 stress 0.4730423
## Run 15 stress 0.4721186
## Run 16 stress 0.2377542
## Run 17 stress 0.2228147
## ... Procrustes: rmse 0.003233775 max resid 0.04351447
## Run 18 stress 0.2231378
## ... Procrustes: rmse 0.004597609 max resid 0.06113926
## Run 19 stress 0.2287039
## Run 20 stress 0.2297875
## *** Solution reached
## Run 0 stress 0.1436293
## Run 1 stress 0.1486094
## Run 2 stress 0.1443403
## Run 3 stress 0.1442081
## Run 4 stress 0.1531921
## Run 5 stress 0.1502679
## Run 6 stress 0.1612787
## Run 7 stress 0.1566424
## Run 8 stress 0.1570929
## Run 9 stress 0.1486384
## Run 10 stress 0.1535379
## Run 11 stress 0.159447
## Run 12 stress 0.1464486
## Run 13 stress 0.1544913
## Run 14 stress 0.1461988
## Run 15 stress 0.1576453
## Run 16 stress 0.1496064
## Run 17 stress 0.1564018
## Run 18 stress 0.1480887
## Run 19 stress 0.1493734
## Run 20 stress 0.1494265
## *** No convergence -- monoMDS stopping criteria:
## 18: stress ratio > sratmax
## 2: scale factor of the gradient < sfgrmin
## Run 0 stress 0.09709427
## Run 1 stress 0.09754663
## ... Procrustes: rmse 0.01026544 max resid 0.09711669
## Run 2 stress 0.09747948
## ... Procrustes: rmse 0.009486836 max resid 0.1245058
## Run 3 stress 0.09754762
## ... Procrustes: rmse 0.01036333 max resid 0.09739683
## Run 4 stress 0.09709435
## ... Procrustes: rmse 0.0001189573 max resid 0.0008117857
## ... Similar to previous best
## Run 5 stress 0.0975505
## ... Procrustes: rmse 0.0101535 max resid 0.09699696
## Run 6 stress 0.0973508
## ... Procrustes: rmse 0.009563138 max resid 0.09722738
## Run 7 stress 0.0974769
## ... Procrustes: rmse 0.00934962 max resid 0.1239022
## Run 8 stress 0.09755259
## ... Procrustes: rmse 0.01017122 max resid 0.09697986
## Run 9 stress 0.09767318
## Run 10 stress 0.09744191
## ... Procrustes: rmse 0.009506244 max resid 0.09224772
## Run 11 stress 0.09727104
## ... Procrustes: rmse 0.004930243 max resid 0.05705233
## Run 12 stress 0.09765486
## Run 13 stress 0.09765213
## Run 14 stress 0.09771143
## Run 15 stress 0.0972685
## ... Procrustes: rmse 0.004958955 max resid 0.0576244
## Run 16 stress 0.09822962
## Run 17 stress 0.09705864
## ... New best solution
## ... Procrustes: rmse 0.002956479 max resid 0.0400573
## Run 18 stress 0.09709413
## ... Procrustes: rmse 0.002939072 max resid 0.03999258
## Run 19 stress 0.09762706
## Run 20 stress 0.09709425
## ... Procrustes: rmse 0.00293682 max resid 0.04000608
## *** No convergence -- monoMDS stopping criteria:
## 6: no. of iterations >= maxit
## 12: stress ratio > sratmax
## 2: scale factor of the gradient < sfgrmin
## Run 0 stress 0.07047178
## Run 1 stress 0.07102312
## Run 2 stress 0.07110785
## Run 3 stress 0.0714534
## Run 4 stress 0.07086136
## ... Procrustes: rmse 0.006679332 max resid 0.06491642
## Run 5 stress 0.07039018
## ... New best solution
## ... Procrustes: rmse 0.003502336 max resid 0.03262194
## Run 6 stress 0.07038655
## ... New best solution
## ... Procrustes: rmse 0.0008773334 max resid 0.01070979
## Run 7 stress 0.07025201
## ... New best solution
## ... Procrustes: rmse 0.004648263 max resid 0.06547353
## Run 8 stress 0.07026352
## ... Procrustes: rmse 0.001136088 max resid 0.00953059
## ... Similar to previous best
## Run 9 stress 0.07027176
## ... Procrustes: rmse 0.002038886 max resid 0.02091927
## Run 10 stress 0.07101319
## Run 11 stress 0.0702583
## ... Procrustes: rmse 0.0003942782 max resid 0.003288427
## ... Similar to previous best
## Run 12 stress 0.07101966
## Run 13 stress 0.07025307
## ... Procrustes: rmse 0.0008700268 max resid 0.008826028
## ... Similar to previous best
## Run 14 stress 0.0702645
## ... Procrustes: rmse 0.001500786 max resid 0.01063863
## Run 15 stress 0.07044296
## ... Procrustes: rmse 0.006090172 max resid 0.06699288
## Run 16 stress 0.07156488
## Run 17 stress 0.07116915
## Run 18 stress 0.07040376
## ... Procrustes: rmse 0.003543406 max resid 0.03344676
## Run 19 stress 0.0714708
## Run 20 stress 0.07105251
## *** Solution reached
## Run 0 stress 0.05433226
## Run 1 stress 0.05440777
## ... Procrustes: rmse 0.009616066 max resid 0.09068029
## Run 2 stress 0.0551087
## Run 3 stress 0.05506838
## Run 4 stress 0.05435078
## ... Procrustes: rmse 0.001966295 max resid 0.01177023
## Run 5 stress 0.05450461
## ... Procrustes: rmse 0.00752855 max resid 0.07160852
## Run 6 stress 0.05441785
## ... Procrustes: rmse 0.006554141 max resid 0.08895075
## Run 7 stress 0.05440365
## ... Procrustes: rmse 0.009338949 max resid 0.08697532
## Run 8 stress 0.0544859
## ... Procrustes: rmse 0.01612902 max resid 0.08247204
## Run 9 stress 0.05444043
## ... Procrustes: rmse 0.008025015 max resid 0.08414216
## Run 10 stress 0.05448708
## ... Procrustes: rmse 0.01598595 max resid 0.08083864
## Run 11 stress 0.05440275
## ... Procrustes: rmse 0.01694273 max resid 0.09308145
## Run 12 stress 0.05482016
## ... Procrustes: rmse 0.01635894 max resid 0.08640639
## Run 13 stress 0.05433185
## ... New best solution
## ... Procrustes: rmse 0.001086522 max resid 0.007105274
## ... Similar to previous best
## Run 14 stress 0.05441251
## ... Procrustes: rmse 0.01663053 max resid 0.09510967
## Run 15 stress 0.05449811
## ... Procrustes: rmse 0.01544921 max resid 0.07965806
## Run 16 stress 0.05447836
## ... Procrustes: rmse 0.005970604 max resid 0.05415409
## Run 17 stress 0.05448382
## ... Procrustes: rmse 0.01568316 max resid 0.08021311
## Run 18 stress 0.05444392
## ... Procrustes: rmse 0.007005956 max resid 0.08447444
## Run 19 stress 0.05439602
## ... Procrustes: rmse 0.005099943 max resid 0.05931647
## Run 20 stress 0.05440373
## ... Procrustes: rmse 0.009240614 max resid 0.08775656
## *** Solution reached
## Run 0 stress 0.04561447
## Run 1 stress 0.04591376
## ... Procrustes: rmse 0.01185613 max resid 0.09519358
## Run 2 stress 0.0456304
## ... Procrustes: rmse 0.008583637 max resid 0.09847771
## Run 3 stress 0.04581267
## ... Procrustes: rmse 0.005996179 max resid 0.04583005
## Run 4 stress 0.04625355
## Run 5 stress 0.04557202
## ... New best solution
## ... Procrustes: rmse 0.007123406 max resid 0.09781215
## Run 6 stress 0.04627167
## Run 7 stress 0.04571769
## ... Procrustes: rmse 0.008947837 max resid 0.0918862
## Run 8 stress 0.04612425
## Run 9 stress 0.04640134
## Run 10 stress 0.04650936
## Run 11 stress 0.04559427
## ... Procrustes: rmse 0.002769385 max resid 0.02483894
## Run 12 stress 0.04572434
## ... Procrustes: rmse 0.008604123 max resid 0.09044336
## Run 13 stress 0.04615068
## Run 14 stress 0.04588088
## ... Procrustes: rmse 0.01125041 max resid 0.09493494
## Run 15 stress 0.04563303
## ... Procrustes: rmse 0.003525593 max resid 0.02701594
## Run 16 stress 0.04584846
## ... Procrustes: rmse 0.008917234 max resid 0.07743574
## Run 17 stress 0.04556203
## ... New best solution
## ... Procrustes: rmse 0.00156025 max resid 0.009410429
## ... Similar to previous best
## Run 18 stress 0.04647915
## Run 19 stress 0.04563358
## ... Procrustes: rmse 0.002864333 max resid 0.01316102
## Run 20 stress 0.04583206
## ... Procrustes: rmse 0.01389679 max resid 0.09638363
## *** Solution reached
## Run 0 stress 0.03951312
## Run 1 stress 0.03955809
## ... Procrustes: rmse 0.003166683 max resid 0.01377554
## Run 2 stress 0.04097779
## Run 3 stress 0.04018418
## Run 4 stress 0.04007966
## Run 5 stress 0.04085249
## Run 6 stress 0.04076794
## Run 7 stress 0.04001254
## ... Procrustes: rmse 0.01071903 max resid 0.05097976
## Run 8 stress 0.04072747
## Run 9 stress 0.04052628
## Run 10 stress 0.04093845
## Run 11 stress 0.03967428
## ... Procrustes: rmse 0.006655434 max resid 0.03328485
## Run 12 stress 0.04076596
## Run 13 stress 0.03970225
## ... Procrustes: rmse 0.006581284 max resid 0.07138278
## Run 14 stress 0.03973123
## ... Procrustes: rmse 0.00457872 max resid 0.02005867
## Run 15 stress 0.04058963
## Run 16 stress 0.04019474
## Run 17 stress 0.03988703
## ... Procrustes: rmse 0.007349436 max resid 0.04051853
## Run 18 stress 0.04104897
## Run 19 stress 0.03954788
## ... Procrustes: rmse 0.008420895 max resid 0.1037123
## Run 20 stress 0.04018163
## *** No convergence -- monoMDS stopping criteria:
## 20: no. of iterations >= maxit
## Run 0 stress 0.03474612
## Run 1 stress 0.03582044
## Run 2 stress 0.03498145
## ... Procrustes: rmse 0.0081422 max resid 0.06983254
## Run 3 stress 0.03495153
## ... Procrustes: rmse 0.009618641 max resid 0.1049364
## Run 4 stress 0.03590216
## Run 5 stress 0.0363347
## Run 6 stress 0.03494025
## ... Procrustes: rmse 0.01418837 max resid 0.1056096
## Run 7 stress 0.03532195
## Run 8 stress 0.03560952
## Run 9 stress 0.0356108
## Run 10 stress 0.03531885
## Run 11 stress 0.03540635
## Run 12 stress 0.03516325
## ... Procrustes: rmse 0.01061268 max resid 0.1081029
## Run 13 stress 0.03529965
## Run 14 stress 0.03558062
## Run 15 stress 0.03524526
## ... Procrustes: rmse 0.008307538 max resid 0.04248
## Run 16 stress 0.03528605
## Run 17 stress 0.03498036
## ... Procrustes: rmse 0.006324409 max resid 0.03143328
## Run 18 stress 0.03500067
## ... Procrustes: rmse 0.007852123 max resid 0.04148387
## Run 19 stress 0.03509831
## ... Procrustes: rmse 0.01018218 max resid 0.09295522
## Run 20 stress 0.0349813
## ... Procrustes: rmse 0.006623939 max resid 0.04036651
## *** No convergence -- monoMDS stopping criteria:
## 20: no. of iterations >= maxit
## Run 0 stress 0.03098824
## Run 1 stress 0.03090659
## ... New best solution
## ... Procrustes: rmse 0.006674616 max resid 0.04173228
## Run 2 stress 0.03146113
## Run 3 stress 0.03119189
## ... Procrustes: rmse 0.01481912 max resid 0.08172965
## Run 4 stress 0.03192555
## Run 5 stress 0.03135098
## ... Procrustes: rmse 0.01413882 max resid 0.04802066
## Run 6 stress 0.03117608
## ... Procrustes: rmse 0.009615589 max resid 0.07672595
## Run 7 stress 0.03125503
## ... Procrustes: rmse 0.01427534 max resid 0.0591329
## Run 8 stress 0.03126717
## ... Procrustes: rmse 0.01470226 max resid 0.07015532
## Run 9 stress 0.03150747
## Run 10 stress 0.03155611
## Run 11 stress 0.03115034
## ... Procrustes: rmse 0.007648187 max resid 0.04033101
## Run 12 stress 0.03125622
## ... Procrustes: rmse 0.01157045 max resid 0.05370108
## Run 13 stress 0.03100039
## ... Procrustes: rmse 0.01329824 max resid 0.06402712
## Run 14 stress 0.03187234
## Run 15 stress 0.03155899
## Run 16 stress 0.03148414
## Run 17 stress 0.03159434
## Run 18 stress 0.03216149
## Run 19 stress 0.0311361
## ... Procrustes: rmse 0.01315832 max resid 0.1090221
## Run 20 stress 0.03123222
## ... Procrustes: rmse 0.01433109 max resid 0.06351897
## *** No convergence -- monoMDS stopping criteria:
## 20: no. of iterations >= maxit
## Run 0 stress 0.02752796
## Run 1 stress 0.02846168
## Run 2 stress 0.02825818
## Run 3 stress 0.02828048
## Run 4 stress 0.0279855
## ... Procrustes: rmse 0.01570628 max resid 0.07782326
## Run 5 stress 0.02815047
## Run 6 stress 0.02840748
## Run 7 stress 0.02813255
## Run 8 stress 0.02833736
## Run 9 stress 0.02812444
## Run 10 stress 0.02816788
## Run 11 stress 0.02803591
## Run 12 stress 0.02787408
## ... Procrustes: rmse 0.01160137 max resid 0.07454286
## Run 13 stress 0.02812524
## Run 14 stress 0.0280183
## ... Procrustes: rmse 0.01227147 max resid 0.07013725
## Run 15 stress 0.02825886
## Run 16 stress 0.02857985
## Run 17 stress 0.02856852
## Run 18 stress 0.02804476
## Run 19 stress 0.02790595
## ... Procrustes: rmse 0.009173516 max resid 0.05111299
## Run 20 stress 0.0283807
## *** No convergence -- monoMDS stopping criteria:
## 20: no. of iterations >= maxit
## [1] 0.22278198 0.14362935 0.09705864 0.07025201 0.05433185 0.04556203 0.03951312 0.03474612 0.03090659
## [10] 0.02752796
## Run 0 stress 0.09709427
## Run 1 stress 0.09752464
## ... Procrustes: rmse 0.01008714 max resid 0.1271265
## Run 2 stress 0.09705968
## ... New best solution
## ... Procrustes: rmse 0.00295956 max resid 0.04002841
## Run 3 stress 0.09790286
## Run 4 stress 0.09764614
## Run 5 stress 0.09754717
## ... Procrustes: rmse 0.009416431 max resid 0.09708316
## Run 6 stress 0.09744272
## ... Procrustes: rmse 0.008364005 max resid 0.09190001
## Run 7 stress 0.09735173
## ... Procrustes: rmse 0.008519178 max resid 0.09689312
## Run 8 stress 0.09999102
## Run 9 stress 0.09730257
## ... Procrustes: rmse 0.004945427 max resid 0.05715123
## Run 10 stress 0.1030611
## Run 11 stress 0.0973513
## ... Procrustes: rmse 0.008480727 max resid 0.09678826
## Run 12 stress 0.09744229
## ... Procrustes: rmse 0.008507725 max resid 0.09253177
## Run 13 stress 0.09744197
## ... Procrustes: rmse 0.008521106 max resid 0.09255885
## Run 14 stress 0.09762664
## Run 15 stress 0.09747689
## ... Procrustes: rmse 0.01018135 max resid 0.1252437
## Run 16 stress 0.0975473
## ... Procrustes: rmse 0.009412099 max resid 0.09706666
## Run 17 stress 0.09709419
## ... Procrustes: rmse 0.002960429 max resid 0.04005042
## Run 18 stress 0.09726846
## ... Procrustes: rmse 0.00399885 max resid 0.05747728
## Run 19 stress 0.09764679
## Run 20 stress 0.09754703
## ... Procrustes: rmse 0.009356695 max resid 0.09694469
## Run 21 stress 0.09812755
## Run 22 stress 0.09735093
## ... Procrustes: rmse 0.008465 max resid 0.09679764
## Run 23 stress 0.09793137
## Run 24 stress 0.09709429
## ... Procrustes: rmse 0.002980367 max resid 0.04018898
## Run 25 stress 0.1030722
## Run 26 stress 0.0973506
## ... Procrustes: rmse 0.008476784 max resid 0.09681038
## Run 27 stress 0.09735836
## ... Procrustes: rmse 0.008726471 max resid 0.0973588
## Run 28 stress 0.09709419
## ... Procrustes: rmse 0.002942892 max resid 0.03993169
## Run 29 stress 0.09730249
## ... Procrustes: rmse 0.004965041 max resid 0.05737245
## Run 30 stress 0.09747798
## ... Procrustes: rmse 0.01030636 max resid 0.1260115
## Run 31 stress 0.1036483
## Run 32 stress 0.09785358
## Run 33 stress 0.09754711
## ... Procrustes: rmse 0.009371423 max resid 0.09692902
## Run 34 stress 0.09709413
## ... Procrustes: rmse 0.002955177 max resid 0.0400403
## Run 35 stress 0.0976721
## Run 36 stress 0.09755285
## ... Procrustes: rmse 0.009127096 max resid 0.09643863
## Run 37 stress 0.09709445
## ... Procrustes: rmse 0.002961864 max resid 0.04000355
## Run 38 stress 0.09744179
## ... Procrustes: rmse 0.008477265 max resid 0.09237306
## Run 39 stress 0.09735091
## ... Procrustes: rmse 0.008520017 max resid 0.09688551
## Run 40 stress 0.0976762
## Run 41 stress 0.09953752
## Run 42 stress 0.09759276
## Run 43 stress 0.09754511
## ... Procrustes: rmse 0.01117335 max resid 0.1293348
## Run 44 stress 0.0974427
## ... Procrustes: rmse 0.008428997 max resid 0.09208082
## Run 45 stress 0.09709408
## ... Procrustes: rmse 0.002941022 max resid 0.03993722
## Run 46 stress 0.09762782
## Run 47 stress 0.09709437
## ... Procrustes: rmse 0.002940994 max resid 0.039895
## Run 48 stress 0.09736839
## ... Procrustes: rmse 0.008017193 max resid 0.09617392
## Run 49 stress 0.09990943
## Run 50 stress 0.09988678
## Run 51 stress 0.09730263
## ... Procrustes: rmse 0.004947315 max resid 0.05709419
## Run 52 stress 0.09744247
## ... Procrustes: rmse 0.008511408 max resid 0.09252669
## Run 53 stress 0.09859683
## Run 54 stress 0.09709454
## ... Procrustes: rmse 0.002949577 max resid 0.03993896
## Run 55 stress 0.09754722
## ... Procrustes: rmse 0.009329974 max resid 0.09699089
## Run 56 stress 0.09765502
## Run 57 stress 0.1031211
## Run 58 stress 0.09762715
## Run 59 stress 0.09735224
## ... Procrustes: rmse 0.008374446 max resid 0.09653822
## Run 60 stress 0.09765229
## Run 61 stress 0.1017665
## Run 62 stress 0.1059232
## Run 63 stress 0.09778261
## Run 64 stress 0.0976887
## Run 65 stress 0.09747787
## ... Procrustes: rmse 0.01021409 max resid 0.125621
## Run 66 stress 0.09740409
## ... Procrustes: rmse 0.007518059 max resid 0.0958859
## Run 67 stress 0.09868929
## Run 68 stress 0.09771011
## Run 69 stress 0.09706021
## ... Procrustes: rmse 0.0001494077 max resid 0.001793836
## ... Similar to previous best
## *** Solution reached
# Plot ordination
scale_trap <- c("red", "orange")
names(scale_trap) <- c("pitfall", "sticky")
par(mar = c(4,4,1,1))
plot(ord, display = 'species', type = 'n')
points(ord, display = 'sites', pch = 19, col = scale_trap[m_p_meta$trap_type])
ordiellipse(ord, groups = m_p_meta$trap_type,
label = TRUE, col = scale_trap, lwd = 2)
text(ord, display = 'species')Ordination stress = 0.0970597
devtools::session_info()## - Session info ------------------------------------------------------------------------------------------
## setting value
## version R version 4.1.0 (2021-05-18)
## os Windows 10 x64
## system i386, mingw32
## ui RStudio
## language (EN)
## collate English_United States.1252
## ctype English_United States.1252
## tz America/Los_Angeles
## date 2021-07-27
##
## - Packages ----------------------------------------------------------------------------------------------
## ! package * version date lib source
## P assertthat 0.2.1 2019-03-21 [?] CRAN (R 4.1.0)
## P backports 1.2.1 2020-12-09 [?] CRAN (R 4.1.0)
## P broom 0.7.8 2021-06-24 [?] CRAN (R 4.1.0)
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## P dplyr * 1.0.7 2021-06-18 [?] CRAN (R 4.1.0)
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## P katereR 0.1.0 2021-07-15 [?] Github (katekathrynkat/katereR@a771b5e)
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##
## [1] C:/Users/kathr/Documents/git-repos/lizard-guts-naxos/renv/library/R-4.1/i386-w64-mingw32
## [2] C:/Users/kathr/AppData/Local/Temp/RtmpWykWok/renv-system-library
##
## P -- Loaded and on-disk path mismatch.